Sygnal, a Web Application and AI for Systemic Agronomy Design

The project involved the development of a web tool for systemic agriculture, with a focus on knowledge representation and visualization. The mission took place between April 2018 and December 2020, in collaboration with various research units. The development was supervised by the Information Systems Department (DSI) of INRAE (National Research Institute for Agriculture, Food and Environment).

Tasks & Objectives

As a developer, designer, and IT administrator, my role involved creating a technology suite for knowledge acquisition and exploration. One of the main objectives was to establish a knowledge representation model and develop a tool for visualizing and exploring these knowledge structures.

Success criteria included not only the development of a functional web application but also the creation of a comprehensive knowledge representation model that could be used across various domains and scales. A key objective was to connect knowledge to existing data and manage a complex tech stack. Finally, it was essential to develop a user-friendly interface that could facilitate knowledge exploration.

Actions and Development

My first step was to co-construct a knowledge representation model with the research teams. I then developed a highly configurable web application using TypeScript and Angular 2. For data storage and querying, I used RDF/SPARQL and Neo4j/Cypher. Regular workshops with users facilitated the development process.

Regular exchanges with the project, scientific, and IT teams, as well as with the former development team, facilitated my work. Collaboration with various research units was crucial for developing a common understanding of the knowledge representation model and establishing a shared vocabulary. Despite the complexity of the project and significant technical challenges, implementing the knowledge representation model represented a major challenge but also a learning opportunity.

Key decisions were made collectively during bi-weekly meetings. For the knowledge representation model, I presented a Proof of Concept (POC) before implementing the complete solution.

Results

The results are multiple: creation of the Sygnal tool, which aggregated over 2000 nodes and 24000 relationships, receiving positive feedback from users. An article was published, enhancing the project's visibility. The knowledge representation model allowed for a better understanding of systemic agriculture, while the web application provided a valuable tool for knowledge exploration.

I learned to effectively handle complex knowledge representation, to develop robust web applications, and to create user-friendly interfaces. Finally, the experience of working with systemic agriculture strengthened my understanding of the challenges in agricultural research and improved my ability to communicate complex ideas clearly.

Technical Stack

The technologies used include: TypeScript, Angular 2, Python, HTML/CSS, RDF/SPARQL, Neo4j/Cypher, and Linux systems. For the web application, I chose to use a combination of TypeScript and Angular 2, while other technological choices were made to align with the project objectives. The project, complex in terms of both knowledge representation and web development, required mastery of both technical and domain-specific knowledge. Existing technical challenges also posed a challenge, which I addressed by developing robust solutions and maintaining clear documentation. Finally, learning to effectively use RDF/SPARQL and Neo4j/Cypher constituted an important step in improving the knowledge representation process.